Data, in its various forms, is the cornerstone of any industry. The data industry is expected to generate a staggering 132.2 billion US Dollars by 2020, according to Forbes. It’s quite safe to say that this is where the future lies, as data forms the backbone of many new industries as well.

While there are many new fields in the industry, it is no surprise that many professionals are confused as to which field would have the most demand in the current market. The two major giants are data science and big data analytics. One could always pursue a data science and big data analytics course. But how would one decide which one to choose?

What Does Data Science Do? 

Data science is a field that deals with the processing of data, which involves a lot of steps, like analysis, cleansing, programming, math, statistics, problem-solving capabilities, out-of-the-box thinking techniques, and so on. It is a very broad field, and often involves the retrieval of unique insights from data and visualizing it into a form that can be understood by people. It is an invaluable skill in today’s market, and the number of professionals opting for a data science online course has gone up in recent years.

What Exactly is Big Data Analytics? 

Big data analytics is all about dealing with large volumes of data, which may be structured, unstructured, or a mix of both. This huge amount of raw data cannot be efficiently processed using existing database management systems. It cannot be stored in the memory of a single computer either. Utilising this data to form business insights is the essence of big data analytics.

What Are the Key Differences? 

Data science and big data analytics are both equally interesting career options. And a data science or big data analytics course to further enhance your career options is highly recommended. However, it is important to realise the difference between them to make an informed decision.

•Big data analytics is often used by organisations to improve the overall efficiency, and understanding of the new markets, while data science gives a method to better understand and use the data on time.

•Big data analytics gives users the potential to perform well, while data science brings out insights that create a change.

•Big data relates to new technology, while data science pertains to the strategies used for decision making.

•Big data analytics can analyse the available data and mine the relevant information from huge data sets, while data science allows for making predictions and preparing organisations for the future, training machines to learn without much programming.

While learning about both data science and big data analytics is profitable from a professional standpoint, it has to be said that data science deals with extracting insights that make sense statistically, while big data analytics deals with organizing data. While both require overlapping skills which can be gained through data science and big data analytics courses, people usually learn both, with a bias towards one field, for continued success.

Is One Better Than the Other? 

While the current scenario has a higher demand for data scientists on an average, there is nothing that points to this scale not tipping the other way. Data science is required in fields that require python or SQL coding and working with unstructured data, like:

•Internet searches

•Digital Ads

•Search recommendations

•Image and speech recognition

The tools of a big data analyst are business acumen, creativity, and an analytical mind, and is mostly used in fields like:

•Financial sector



•Travel and healthcare


While no one field can be independent of the other, it is important to realize which of the two, data science or big data analytics, is best for the field you wish to pursue. The data landscape is definitely a promising one, irrespective of how you tip the scale.


Are you ready to build your own career?